Secure multi-party computation involves multiple participant computing devices cooperating to perform a computation based on input from each participant that is to be kept secret from the other participants. Existing techniques provide mechanisms for a participant to verify that a final result of the computation is correct without knowing the secret input data of the other participants.
Distributed ledger systems (DLSs), which can also be referred to as consensus networks, and/or blockchain networks, enable participating entities to securely, and immutably store data. DLSs are commonly referred to as blockchain networks without referencing any particular user case. Examples of types of blockchain networks can include public blockchain networks, private blockchain networks, and consortium blockchain networks. A consortium blockchain network is provided for a select group of entities, which control the consensus process, and includes an access control layer.
Existing secure multi-party computation techniques do not provide any assurance that each participant in the computation is correctly representing their secret input data. A party could therefore influence the final result of the computation, possibly in their favor, by manipulating their own secret input data. Techniques to allow other participants to a multi-party computation to verify that all secret input data is being accurately represented by other participants would be desirable.